Model fit guide / RTX 5080 16GBWeight-based fit estimateReviewed October 7, 2026
16 GB VRAM - Single-card candidate

Local AI model fit for RTX 5080 16GB.

Use this versioned model as a fit candidate, then evaluate it on your workload. Its 14.8B total language-model parameters imply about 7.4 GB of raw weights at 4 bits. This is an analytical estimate, not a measured allocation or a claim that this model is the latest quality winner.

01 / Recommendation

Run this size class.

Candidate to evaluate

Qwen3-14B (versioned baseline)

Use Q4 where supported; context and batch must be measured. Estimate the full runtime allocation before deployment. This candidate has not been measured here at a fixed context length or batch size.

Weight estimate

Weight-only estimate: 7.4 GB at 4 bits, before scales, unquantized tensors, vision components, KV cache and runtime buffers.

Evidence

Official model card gives 14.8B total language-model parameters. Fit labels describe estimated weight headroom only. No tokens-per-second, maximum-context or relative-quality measurement is claimed. Official model card ↗

02 / Alternates

Other deployment options.

A smaller model for more KV-cache headroom

A newer same-size model after workload evaluation

03 / More GPUs

Compare another card.

RTX 3060 12GBRTX 4060 Ti 16GBRTX 3090 24GBRTX 4090 24GBRTX 5090 32GB